• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.329-341
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• 2021

This study derives the risk-Influence factors for subway structures, the basis for the transition from the current subway disaster recovery-oriented maintenance system to a preemptive disaster management system, to reduce risk factors for existing subway structures. To apply reasonable risk assessment techniques, risk influence factors for subway underground structures using statistical information(spatial information) and risk influence factors according to frequency of accidents were selected to derive the risk factors. The significant risk factors were verified through ground subsidence (SI: Subsidence Impact)-based correlation analysis. This process confirmed that the subsidence of the ground was a risk influence factor for the subway structure. The main result of this study is that derive the risk factors to improve the risk factors of subway structures due to the rapid increase in disaster risk factors. The derived risk factors that were expected to affect the depression around subway stations and track structures did not show a noticeable correlation, but the cause of this may be that there is no physical connection between them, but on the other hand, the accumulated data may not accurately record the surrounding depression. Accordingly, in order to evaluate the risk of depression around the station and track, more intensive observation and data accumulation around the structure are required.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.129-136
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• 2023

In this paper, we describe a rule-based risk classification algorithm to perform Risk-based Inspection (RBI) on imported goods at customs. The RBI system is a method to automatically select which cargos have to be inspected and manage potential risks in boarder. In this study, we designed a rule-based risk classification algorithm for RBI solutions and implemented them using the Svelte web application framework. The risk classification algorithm proposed in this paper uses different indicative risk factors such as HS code, country of origin, importer's reliability, trade relationships, and logistics routes to classify cargos into Green, Yellow, and Red channels. To achieve this, we assigned risk categories to each risk factor and randomly generated risk scores within a specific range for each risk category. This system is expected to contribute to the increased efficiency of customs operations and protect public safety by minimizing the risk of imported hazardous materials.

• Journal of Applied Reliability
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• v.10 no.2
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• pp.107-122
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• 2010

Functional safety is the part of the overall safety of a system that depends on the system or equipment operating correctly in response to its inputs, including the safe management of likely operator errors, hardware failures, systematic failures, and environmental changes. One of the essential concepts of functional safety is Safety Integrity Level(SIL). It is defined as a relative level of risk-reduction provided by a safety function, or to specify a target level of risk reduction. In this paper, each element of SIL assessment will be defined. Based on each element, specific process of SIL selection will be established by using flowchart. The flowchart provides a SIL assessment guideline for functional safety engineers. The proposed theory will be verified by applying to a oil refining plant for SIL assessment.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.895-904
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• 2015

This paper presents a probabilistic approach of reliability evaluation and economic assessment for solving transmission network expansion planning problems. Three methods are proposed for TNEP, which are reorganizing the existing power system focused on the buses of interest, selecting candidates using modified system operating state method with healthy, marginal and at-risk states, and finally choosing the optimal alternative using cost-optimization method. TNEP candidates can be selected based on the state reliability such as sufficient and insufficient indices, as proposed in this paper. The process of economic assessment involves the costs of construction, maintenance and operation, congestion, and outage. The case studies are carried out with modified IEEE-24 bus system and Jeju island power system expansion plan in Korea, to verify the proposed methodology.

• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.21-26
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• 1997

Korea Atomic Energy Research Institute (KAERI) developed a risk monitor called Risk Monster which supports for plant operators and maintenance schedulers to monitor plant risk and to avoid high peak risk by rearranging maintenance work schedule. Risk Monster can update the plant risk continuously according to the change of system/component configuration since Risk Monster reevaluates the plant risk based on the Probabilistic Safety Assessment (PSA) results. A brief description of Risk Monster is provided. The PSA model of UCN 3, 4 nuclear power plant was converted by KAERI to Risk Monster model. Using this Risk Monster model, a feasibility study of the on-line maintenance of an Essential Service Water (ESW) pump was performed. On-line maintenance of one ESW pump has been shown to be acceptably safe, and has economic benefits. In addition, it is not a violation of technical specification to continue plant operation with an out-of-service ESW pump.

• Smart Structures and Systems
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• v.26 no.2
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

• Nuclear Engineering and Technology
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• v.37 no.1
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• pp.109-117
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• 2005

Limiting conditions for operations (LCOs) are evaluated dynamically using the tool of system dynamics. The LCOs de-fine the allowed outage times (AOTs) and the actions to be taken if the repair cannot be completed within the AOT. System dynamics has been developed to analyze the dynamic reliability of a complicated system. System dynamics using Vensim software have been applied to LCOs assessment for an example system, the auxiliary feed water system of a reference nuclear power plant. Analysis results of both full power operation and shutdown operation have been compared for a measure of core damage frequency. The framework developed in this study has been shown to be very flexible in that it can be applied to assess LCOs quantitatively under any operational context of the TS in FSAR.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.16 no.4
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• pp.413-427
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• 2006

It is necessary to study and develop guidelines for providing comfort and health indoor air quality for office workers since air-tight envelope system of current office building may cause poor indoor air quality. The purpose of this study is to propose guideline for volatile organic compounds in office base on the field study, human health risk assessment and cost-benefit analysis. The field study was conducted to survey the concentrations of volatile organic compounds in indoor air of 69 offices from June to September, 2005 in Seoul and Gyeonggi-do. The rate of excess to guideline of volatile organic compounds in indoor air of new apartment on the Ministry of Environment in Korea(MOE) was surveyed 37.6% for benzene, 6.8% for toluene, and 1.5% for ethylbenzene. As the result of human health risk assessment, mean cancer risk did not exceed 10-6 which is guideline of US.EPA. Also, total hazard index did not exceed 1 which is guideline of US.EPA. Through the cost-benefit analysis of angle on the social-economics to verify the necessary to establish the standards of volatile organic compounds for improvement and development of indoor air quality in office, the present value of benefit was higher than the present value of cost. With the above considerations in mind, it is suggested that the field study for indoor air quality in offices should be expanded and human health risk assessment and cost-benefit analysis be performed th offer scientific data for decision-making of policy for improvement and management of indoor air quality in office.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.59-73
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• 2016

The demand for subsurface transport is increasing. The users and the operators of road tunnels are exposed to risks with different causes. One main cause, however, is the traffic situation in the event of accidents. The importance of a Quantified Risk Assessment is increasing to quantify the safety of road tunnels and to balance the requirements (capacity, reliability, availability, maintainability and safety) of various stakeholders. Although there are classical methods for risk assessments, such as ETA and FTA. These methods are used for relatively simple cases because it could not relevantly reflect the diversity and relationship of the parameters. Therefore, a quantitative risk assessment based on Bayesian Probabilistic Networks considering interdependence between the parameters of a complex underground system as a double deck tunnel is provided.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.957-964
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• 2013

This research is on the methodology of flood risk assessment using flooding characteristic values. Necessity of design magnitude for flood control considering floods was judged by plotting peak flow with respect to frequency and duration, and flooding magnitude was defined with 6 flooding characteristic values which were proposed to be significant factors when assessing flooding magnitude. Precipitation data used in the assessment modeling were applied by combining all the possible precipitation events. After overlapping the simulated results with precipitation matrix by flooding characteristic values, contour map was drawn, and Flooding characteristic contour graph for possible rainfall events were suggested in respect of all possible precipitation. Flooding characteristic contour graph for possible rainfall events was confirmed that reducing of damage magnitude of each flood characteristic value was figured out easily. The flood risk assessment methods suggested in this study would be a good reference for urban drainage system design, which only focuses on pipe conduit.